The intensive care unit (ICU) is broadly viewed as the epicentre of
a high reliability organisation (HRO) in a healthcare system. After all, ICU
clinicians care for the sickest patients with the most complex, high technology
therapies and monitors. Moreover, the Leapfrog Group developed standards for
the best models of care in the ICU – an intensivist led-care team (Leapfrog
Group 2011).

However, the facts tell a very different story about reliability in
the ICU. We know that only 42 percent of hospitals in the USA that responded to
the Leapfrog Group’s hospital survey reported compliance with the ICU Physician
Staffing standard (unpublished data, Leapfrog Group, February 17, 2014).
Therapies to prevent avoidable harm are delivered erratically. For example, of
patients at risk for ventilator-associated lung injury, only 20 percent to 40
percent receive appropriate, weight-based tidal volumes on the ventilator
(Pronovost et al. 2010). Clinicians may also be overly optimistic about the
quality of care they provide. Scales and co-workers (2011) found that only 50%
of eligible ventilated ICU patients had the head of their bed elevated to > 30
degrees before the quality improvement intervention was implemented. Most
importantly, patients continue to experience harm at an unacceptable rate that far
exceeds the level of harm in an HRO; avoidable error is considered to be the
third leading cause of death in the USA (Wachter et al. 2013).

The HRO model was developed by examining commonalities of
industries that require near error-free performance, such as commercial
aviation and nuclear power. Despite being very risky, HROs create systems to
manage the complexity of technology and task performance (Sutcliffe 2011). High
reliability organisations apply systems engineering to ensure the technology,
work process, and culture are all carefully integrated and orchestrated to
deliver high levels of safety. Compare this to the current ICU system design
recommended by the Leapfrog Group. In this model, the core of the system, the
data storage and knowledge management system, is the intensivist and the care team.
This model has evolved naturally with the development of critical care, but its
deficiencies are obvious. It relies on the flawless performance of an
intensivist-led team, a model that depends on the heroic performance of
individuals. A model we have argued is outdated, under-engineered, and doomed
to fail at high frequency (Pronovost et al. 2014). If the ICU is to reduce harm
and work toward becoming an HRO, the system design will need to mature.

Systems engineering has been applied successfully in HROs to
virtually eliminate errors and catastrophic failure. Systems of systems (SoS)
have been created, in which many subsystems are integrated, and become
interdependent to reduce harmful errors and improve efficiency. Like an HRO,
safe and high quality healthcare depends on the interaction of many systems,
aligned purposefully to achieve common safety and quality care goals (Shekelle
et al. 2013). By applying systems principles, we believe it is possible to
create, a safe, productive SoS for ICU care (Christianson et al. 2011).

We have developed a comprehensive plan to start integrating the
many constituent subsystems that comprise ICU care to create a SoS. Our plan is
based on the US Navy’s submarine force known as Advanced Processor Build (APB)/Acoustic
Rapid COTS Insertion plan for submarines (Stevens 2008), which began in 1998
and continues today. Our plan will design, implement, iterate, and evaluate a
systems approach, articulating the necessary components and partners. The SoS
plan, adapted for healthcare, involves the following seven major elements (see
Figure 1).

1. Concept for Integrated Healthcare
Delivery System.

The high-level description of an integrated healthcare delivery system
is a system of systems (SoS). The constituent elements that comprise this SoS
include all subsystems, such as ICU settings (eg, surgical ICU, medical ICU),
operating rooms, emergency departments, primary care offices, home care.
Subsystems are identified and their mutual interactions described. Subsystems
are characterised as ‘black boxes’ with appropriate inputs and outputs between
each box.

2. Concept for Integrated Healthcare
Delivery Subsystems.

The subsystems are detailed using a Concept of Operations (CONOPS).
A CONOPS provides the vision and purpose for the (sub)system and an analysis of
the system’s operational needs and mission requirements. The CONOPS describes the
roles and activities of each user, the operational process, and operational command structures.Importantly, key performance parameters, interdependenciesbetween subsystems, and thefacilities, equipment, hardware, software, andpersonnel associated with the subsystem aredefined.
The CONOPS also describes knowngaps with
existing capabilities. These gaps areflags
for innovators to develop new solutionsthat
fulfil the vision described in the CONOPS.Healthcare
has yet to produce such detailedCONOPS and
this work will advance the field.

3. Call for Innovation for Candidate Solutions.

Innovators
across industry and academia are asked to develop candidate solutions to the
system gaps that are identified in stage 2 of the model. In contrast to the
current top down approaches, the SoS program provides a goal-directed approach,
focusing on a problem to be solved or a job to be done.

4. Learning Laboratory.

The
Agency for Healthcare Research and Quality (AHRQ) defines a learning laboratory
as: “…places and professional networks that allow multidisciplinary teams to
identify interrelated threats to patient safety, stretch professional boundaries,
envision bold design innovations, and take advantage of brainstorming and rapid
prototyping techniques that other leading-edge sectors of the economy employ…” (U.S.
Department of Health and Human Services 2013). The Johns Hopkins Armstrong
Institute implemented a robust process to analyse novel candidate solutions to fill
gaps across four dimensions: culture, workflow, technology, and learning and
accountability. These four dimensions characterise the key aspects of
integrated socio-technical solutions, purposefully designed and integrated to enhance
overall safety and quality in the ICU.

5. Systems Integration.

After
an evaluation in the Learning Laboratory, candidate solutions need further
refinement before integration into an operational production system. Academia
(eg, Johns Hopkins Armstrong Institute) and a Systems Integrator, such as the
role that Lockheed Martin or Boeing serve in aviation, should collaborate on
additional laboratory assessments and production level refinements. The goal of
this interaction is to develop a product that can be broadly implemented. It is
important to understand that this development includes both technical and social
components. The product must be rigorously tested and evaluated to ensure the
integration matches the needed performance and is aligned with the key
performance parameters identified in the CONOPS.

6. Production Integrated Healthcare Delivery System.

The
vision described in elements one and two is realised here. The capabilities
defined previously are integrated into a comprehensive care delivery model that
is used in clinical settings. Because of the magnitude of building a healthcare
SoS, it will be impossible to immediately implement a full set of integrated
systems envisioned in Element 1. Instead, project teams must incrementally
develop and build capabilities in sequence by repeatedly cycling through the
plan (Figure 1).

7. Outcomes Analysis.

Measurement
in clinical settings is essential for benchmarking performance of new systems and
allows continuous improvement of overall SoS performance. Each successive pass through
the development cycle described in Figure 1, will reveal unanticipated
performance deficits and unintended consequences. Accordingly, an outcomes
analysis is essential for keeping the overall effort precisely focused on the
ultimate vision. This analysis allows the focus to adjust for changes in the
challenges and gaps that are revealed in real-world settings.

While
this SoS approach is mature in other industries, it is grossly underdeveloped
in healthcare. Neither clinicians nor technology companies can do this alone.
Healthcare needs a learning laboratory that convenes clinicians, engineers,
researchers and others to design the healthcare systems patients deserve,
clinicians want, and the country needs.

Source of Funding and Conflicts of Interest:

There
was no funding. Dr. Pronovost reports receiving grant or contract support from
the Agency for Healthcare Research and Quality, the Gordon and Betty Moore
Foundation (research related to patient safety and quality of care), the
National Institutes of Health (acute lung injury research), and the American Medical
Association Inc. (improve blood pressure control); honoraria from various
healthcare organisations for speaking on patient safety and quality (the Leigh
Bureau manages most of these engagements); book royalties from the Penguin
Group for his book Safe Patients, Smart Hospitals; consultant fees as a
strategic advisor to the Gordon and Betty Moore Foundation; and stock and fees
to serve as a director for Cantel Medical. Dr. Pronovost is a founder of
Patient Doctor Technologies, a startup company that seeks to enhance the
partnership between patients and clinicians with an application called
Doctella. Dr. Ravitz and Dr. Sapirstein report no conflicts of interest.

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